Custom Image Recognition API Introduction | Chooch
Learn more: https://www.chooch.com/
Join us for a quick intro to the custom image recognition API from Chooch AI.
Read AI API Documentation: https://www.chooch.com/api/
In this video, we are testing an image recognition perception that we created before on the Chooch AI Dashboard. Also, we explain the API response fields in detail.
Our team can help you to quickly create image and object recognition solutions with visual AI in weeks, not years. From inventory to authentication, microscopic to satellite, actions to radiology, by training our AI to recognize objects in still images or video, we generate results for our customers.
Here's the transcript:
Hi in this video we are going to go over the Custom image Recognition API from the Chooch AI Documentation page.
I'm gonna scroll here, to the URL post
Section and copy the URL field and paste it to my text editor. This time we have the model ID, the API key, and the image URL.
This time in order to apply our image recognition API, we need an image perception that’s in our account. I'm going to click on Training on the Chooch dashboard and then select “my image”. I have a car or truck perception here. I'm just going to copy the model idea of this perception and paste it into the model ID field in the text editor
We need a car or truck image for testing. So, I have an image here. I’ll copy this URL, and paste it to the image URL field.
Lastly, I need to copy my API key then paste it. I’ll copy the entire URL, and paste it into my web browser, then hit enter.
And this is our JSON response. We Again have the status field as okay which means it’s successful
The URL field is the URL of the image. The model ID, this model runs field above the model ID field refers to the model ID we used here.
The Perception name, which is car-or-truck is represented here by the modal- title field.
The prediction results can be found under predictions. We have modal id again. We also have class id here. The class id represents the class name field of the perception. As you can see my class name was truck 444. It’s displaying like this because it’s predicted as a truck. Class title is the same as class id. And the score is the prediction score of this image
Let’s open the API documentation and you can see that the prediction type is image for this API call. And that is the Custom Image Recognition API from Chooch AI API Documentation.
Contact us at: https://www.chooch.com/contact-us/
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#AIVision #EmergingTechnologies #VisionAI #ArtificialIntelligence #MachineLearning #DeepLearning #EdgeComputing #CloudAI #EdgeAI #AI #Chooch
Learn more: https://www.chooch.com/
Join us for a quick intro to the custom image recognition API from Chooch AI.
Read AI API Documentation: https://www.chooch.com/api/
In this video, we are testing an image recognition perception that we created before on the Chooch AI Dashboard. Also, we explain the API response fields in detail.
Our team can help you to quickly create image and object recognition solutions with visual AI in weeks, not years. From inventory to authentication, microscopic to satellite, actions to radiology, by training our AI to recognize objects in still images or video, we generate results for our customers.
Here’s the transcript:
Hi in this video we are going to go over the Custom image Recognition API from the Chooch AI Documentation page.
I’m gonna scroll here, to the URL post
Section and copy the URL field and paste it to my text editor. This time we have the model ID, the API key, and the image URL.
This time in order to apply our image recognition API, we need an image perception that’s in our account. I’m going to click on Training on the Chooch dashboard and then select “my image”. I have a car or truck perception here. I’m just going to copy the model idea of this perception and paste it into the model ID field in the text editor
We need a car or truck image for testing. So, I have an image here. I’ll copy this URL, and paste it to the image URL field.
Lastly, I need to copy my API key then paste it. I’ll copy the entire URL, and paste it into my web browser, then hit enter.
And this is our JSON response. We Again have the status field as okay which means it’s successful
The URL field is the URL of the image. The model ID, this model runs field above the model ID field refers to the model ID we used here.
The Perception name, which is car-or-truck is represented here by the modal- title field.
The prediction results can be found under predictions. We have modal id again. We also have class id here. The class id represents the class name field of the perception. As you can see my class name was truck 444. It’s displaying like this because it’s predicted as a truck. Class title is the same as class id. And the score is the prediction score of this image
Let’s open the API documentation and you can see that the prediction type is image for this API call. And that is the Custom Image Recognition API from Chooch AI API Documentation.
Contact us at: https://www.chooch.com/contact-us/
FOLLOW US ON LINKEDIN:
https://www.linkedin.com/company/chooch
#AIVision #EmergingTechnologies #VisionAI #ArtificialIntelligence #MachineLearning #DeepLearning #EdgeComputing #CloudAI #EdgeAI #AI #Chooch
